Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Mech & Mine Engineering School
Truck/shovel systems are the most common means of extraction of mineral resources in surface mines. The optimal performance of truck/shovel fleets involves a knowledge of mine design, equipment performance characteristics, stochastic systems performance and management theory. This course aims to impart the fundamentals of successful fleet management to professionals charged with the management and control of such operations.
The course consists of seven weeks of online courses, each focusing on key aspects of the fleet management, plus a number of problem-based learning sessions, most of which will be hosted virtually.
Course contact
Course staff
Lecturer
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
This course aims to impart the fundamentals of successful fleet management to professionals charged with the management and control of such operations.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Identify operational safety and health issues for truck/shovel fleet operations on the basis of recent industry case studies.
LO2.
Assess contemporary mining operations in the context of established truck/shovel operating principles.
LO3.
Calculate key performance metrics for truck/shovel fleet operations.
LO4.
Apply the theory of constraints to truck/shovel operations.
LO5.
Develop continuous improvement initiatives for truck/shovel fleet management.
LO6.
Apply life cycle costing principles to shovel/truck operations.
LO7.
Evaluate truck/shovel operations in the context of sustainability principles.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Project | Continuous Improvement project brief | 20% |
6/05/2025 5:00 pm |
| Presentation |
Progress update presentation
|
15% |
26/05/2025 5:00 pm |
| Presentation |
Final Report Presentation
|
15% |
13/06/2025 5:00 pm |
| Paper/ Report/ Annotation | Final Report | 50% |
20/06/2025 5:00 pm |
Assessment details
Continuous Improvement project brief
- Mode
- Written
- Category
- Project
- Weight
- 20%
- Due date
6/05/2025 5:00 pm
- Learning outcomes
- L01, L02, L03
Task description
The project brief involves a scoping study for a Continuous Improvement (CI) project related to a Truck/Shovel fleet at your operation. Opportunities for CI may come from discussions with truck/shovel operators, dispatchers and/or maintainers, or analysis of time usage and production data. If you are not in an operational setting, time usage data from a real case study will be made available to you. You are required to submit a two-page project brief outlining the scope of your intended CI project. In particular, this will estimate the value and ease of capture of the improvement idea. The project brief should cover:
- Description of opportunity: What is the performance gap that you have identified for improvement? Provide a brief description of the evidence available (e.g. benchmark data) to support this gap.
- Value proposition: What is the potential to close the performance gap (e.g. completely solve, partially solve) and what benefits (financial, safety, sustainability) will this bring across the fleet?
- Project evidence and methodology: What data do you require to support evidence of the performance gap? How you intend to collect and process this data? What potential solutions exist to close the performance gap? What is your estimate of the technical and implementation risks associated with this range of solutions?
- Ease of capture: Provide a brief evaluation of the technical and project feasibility of your preferred solution. What risks are involved in implementing the change and how can these be managed?
- Project Plan: Prepare a Gantt chart for the implementation of your CI project. Include project review and sign-off points.
Please refer to Blackboard for a detailed marking criteria.
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submission to Turnitin via Blackboard.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
To facilitate timely feedback to students.
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Electronic Course Profile (ECP), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Progress update presentation
- Online
- Mode
- Activity/ Performance
- Category
- Presentation
- Weight
- 15%
- Due date
26/05/2025 5:00 pm
- Learning outcomes
- L03, L04, L05
Task description
This component involves the reporting of progress via a PowerPoint presentation of no more than 10 minutes covering the following elements:
- Description of CI project
- Progress vs Plan
- Results to date
- Preliminary conclusions and way forward
In this presentation you will highlighting the milestones reached so far and identify any challenges or hurdles encountered and strategies to address them. This presentation will be an opportunity to offer feedback and guidance for the successful completion of the project.
Please refer to Blackboard for a detailed marking criteria.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT for ideation - in particular for generating solutions to the identified performance gap - in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.
Submission guidelines
Submission will be via Teams.
Deferral or extension
You may be able to defer this exam.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Presentation is scheduled and timebound.
Final Report Presentation
- Online
- Mode
- Activity/ Performance
- Category
- Presentation
- Weight
- 15%
- Due date
13/06/2025 5:00 pm
- Learning outcomes
- L04, L05, L06, L07
Task description
For this component you will be required to prepare a 10 minute presentation to be delivered during the workshop online. This final presentation will provide an opportunity to share experiences and generate discussion between the course participants.
This presentation should include the following:
- Introduction with a brief description of the CI project (i.e. details of fleet evaluated and performance gap identified)
- Description of methodology and assumptions
- Results of evaluation and proposed improvements
- Summary of an implementation plan including an estimation of resource requirements for implementation and a Gantt chart highlighting key activities and sign offs required.
- Conclusions and recommendations
Please refer to Blackboard for a detailed marking criteria.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT for ideation - in particular for generating solutions to the identified performance gap - in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.
Submission guidelines
To be delivered during the online workshop.
Deferral or extension
You may be able to defer this exam.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Presentation is scheduled and timebound.
Final Report
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 50%
- Due date
20/06/2025 5:00 pm
- Learning outcomes
- L04, L05, L06, L07
Task description
A final report of no more than 10 pages (excluding coversheet, table of contents/figures and appendices) must be submitted and should include but is not limited to:
- A one-page executive summary
- Introduction with a brief description of the operation and fleet activities implemented.
- Description the selected CI project
- Description of CI value proposition and ease of capture assumptions.
- Results of data evaluation and improvement recommendations
- Implementation plan (included resource requirements and Gantt chart)
- Final conclusions and recommendations
- Relevant references and appendices
Please refer to Blackboard for a detailed marking criteria.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT for ideation - in particular for generating solutions to the identified performance gap - in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.
Submission guidelines
Submission to Turnitin via Blackboard.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
To facilitate timely feedback to students.
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Electronic Course Profile (ECP), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0.00 - 29.99 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 30.00 - 44.99 |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 45.00 - 49.99 |
Demonstrated evidence of developing achievement of course learning outcomes |
| 4 (Pass) | 50.00 - 64.99 |
Demonstrated evidence of functional achievement of course learning outcomes. |
| 5 (Credit) | 65.00 - 74.99 |
Demonstrated evidence of proficient achievement of course learning outcomes. |
| 6 (Distinction) | 75.00 - 84.99 |
Demonstrated evidence of advanced achievement of course learning outcomes. |
| 7 (High Distinction) | 85.00 - 100.00 |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
The Assessment tasks have been designed to be challenging, authentic and complex. Students may use generative AI and/or MT technologies for generating solutions to identified fleet performance gaps, however successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Library resources are available on the UQ Library website.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Week 8 (14 Apr - 20 Apr) |
Seminar |
Kick-Off Seminar Wednesday, 16 April 2025. Learning outcomes: L01, L02 |
Workshop |
Workshop One-day workshop on Wednesday 16 April. Learning outcomes: L01, L02 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments for Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.